{"title":"Overcoming the Christmas tree syndrome","authors":"É. Grégoire, David Ansart","doi":"10.1109/TAI.1999.809836","DOIUrl":"https://doi.org/10.1109/TAI.1999.809836","url":null,"abstract":"We propose a new computational approach to logic-based systems that should reason in a fast but logically sound and complete manner about large-scale complex critical devices and systems that can exhibit unexpected faulty behaviors. The approach is original from at least two points of view. First, it makes use of local search techniques while preserving logical deductive completeness. Second, it proves experimentally efficient for very large knowledge bases thanks to new heuristics in the use of local search techniques.","PeriodicalId":194023,"journal":{"name":"Proceedings 11th International Conference on Tools with Artificial Intelligence","volume":"72 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133003519","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Efficiently detecting arbitrary shaped clusters in image databases","authors":"Dantong Yu, Surojit Chatterjee, A. Zhang","doi":"10.1109/TAI.1999.809785","DOIUrl":"https://doi.org/10.1109/TAI.1999.809785","url":null,"abstract":"Image databases contain data with high dimensions. Finding interesting patterns in these databases poses a very challenging problem because of the scalability, lack of domain knowledge and complex structures of the embedded clusters. High dimensionality adds severely to the scalability problem. In this paper, we introduce WaveCluster/sup +/, a novel approach to apply wavelet-based techniques for clustering high-dimensional data. Using a hash-based data structure to represent the data set, we offer a detailed technique to apply a wavelet transform on the hashed feature space. We demonstrate that the cost of clustering can be reduced dramatically yet maintaining all the advantages of wavelet-based clustering. This hash-based data representation can be applied for any grid-based clustering approaches. The experimental results show the effectiveness and efficiency of our method on high-dimensional data sets.","PeriodicalId":194023,"journal":{"name":"Proceedings 11th International Conference on Tools with Artificial Intelligence","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116653342","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Monitoring of aircraft operation using statistics and machine learning","authors":"Fazel Famili, S. Létourneau","doi":"10.1109/TAI.1999.809800","DOIUrl":"https://doi.org/10.1109/TAI.1999.809800","url":null,"abstract":"This paper describes the use of statistics and machine learning techniques to monitor the performance of commercial aircraft operation. The purpose of this research is to develop methods that can be used to generate reliable and timely alerts so that engineers and fleet specialists become aware of abnormal situations in a large fleet of commercial aircraft that they manage. We introduce three approaches that we have used for monitoring engines and generating alerts. We also explain how additional information can be generated from machine learning experiments so that the parameters influencing the particular abnormal situation and their ranges are also identified and reported. Various benefits of fleet monitoring are explained in the paper.","PeriodicalId":194023,"journal":{"name":"Proceedings 11th International Conference on Tools with Artificial Intelligence","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123613748","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Intelligent Web representatives","authors":"Doug Sapp, Yi Shang","doi":"10.1109/TAI.1999.809770","DOIUrl":"https://doi.org/10.1109/TAI.1999.809770","url":null,"abstract":"We present the design and implementation of an intelligent Web representative based on prevalent Internet and Web technologies. The design includes three parts: natural language parser, knowledge representation, and communication between the user and the computer. With an efficient pseudo-natural language processing, a database of knowledge stored in XML, and the user communication through Microsoft Agent, the intelligent agent can answer questions effectively.","PeriodicalId":194023,"journal":{"name":"Proceedings 11th International Conference on Tools with Artificial Intelligence","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124871936","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Mobile robotics planning using abstract Markov decision processes","authors":"Pierre Laroche, F. Charpillet, R. Schott","doi":"10.1109/TAI.1999.809804","DOIUrl":"https://doi.org/10.1109/TAI.1999.809804","url":null,"abstract":"Markov decision processes have been successfully used in robotics for indoor robot navigation problems. They allow the computation of optimal sequences of actions in order to achieve a given goal, accounting for actuator uncertainties. However, MDPs are unsatisfactory at avoiding unknown obstacles. On the other hand, reactive navigators are particularly adapted to that, and don't need any prior knowledge about the environment, but they are unable to plan the set of actions that will permit the realization of a given mission. We present a new state aggregation technique for Markov decision processes, such that part of the work usually dedicated to the planner is achieved by a reactive navigator. Thus some characteristics of our environments, such as the width of corridors, have not been considered, which allows to cluster states together, significantly reducing the state space. As a consequence, policies are computed faster and are shown to be at least as efficient as optimal ones.","PeriodicalId":194023,"journal":{"name":"Proceedings 11th International Conference on Tools with Artificial Intelligence","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127529235","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Clement S. Allen, S. Stoecklin, P. Bobbie, Qian Chen, Ping Wu
{"title":"An architecture for designing distributed spoken dialogue interfaces","authors":"Clement S. Allen, S. Stoecklin, P. Bobbie, Qian Chen, Ping Wu","doi":"10.1109/TAI.1999.809793","DOIUrl":"https://doi.org/10.1109/TAI.1999.809793","url":null,"abstract":"A spoken dialogue interface allows a user to interact with a computer application using speech. The user engages in a conversation with the application to achieve some goal, for example to obtain travel information or to book theatre tickets. In this paper, we describe an architecture and development environment for designing distributed spoken dialogue interfaces. A distributed spoken dialogue interface allows multiple users, distributed throughout a computer network, to interact with an application using speech. With a distributed spoken dialogue interface, several users engage in a conversation with the application, at different times, to achieve some goal. Our approach to distributed spoken dialogue interfaces is based on the idea of an intelligent agent that coordinates the activities of the multiple users interacting with the application. To support our model of distributed spoken dialogues, we have created a software development environment, JSBB, that can be used to design both distributed and non-distributed spoken dialogue interfaces.","PeriodicalId":194023,"journal":{"name":"Proceedings 11th International Conference on Tools with Artificial Intelligence","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129965530","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
M. Lu, Du Zhang, Hongjun Xu, Ken Tse-yau Lau, Li Lu
{"title":"Protein secondary structure prediction using data mining tool C5","authors":"M. Lu, Du Zhang, Hongjun Xu, Ken Tse-yau Lau, Li Lu","doi":"10.1109/TAI.1999.809774","DOIUrl":"https://doi.org/10.1109/TAI.1999.809774","url":null,"abstract":"This paper reports our experimental results in protein secondary structure prediction using the machine learning software, C5. The accuracy improvement in the prediction of protein secondary structure is the focus of our study. Starting with a target protein with unknown secondary structures, we investigate three different approaches and find that training cases selected based on sequence homology can achieve the highest predictive accuracy of 75% in testing cases. Our result indicates that the method of selecting proteins for the training cases has the most significant impact on predictive accuracy.","PeriodicalId":194023,"journal":{"name":"Proceedings 11th International Conference on Tools with Artificial Intelligence","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123750383","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"An expert system for multiple emotional classification of facial expressions","authors":"M. Pantic, L. Rothkrantz","doi":"10.1109/TAI.1999.809775","DOIUrl":"https://doi.org/10.1109/TAI.1999.809775","url":null,"abstract":"This paper discusses the Integrated System for Facial Expression Recognition (ISFER), which performs facial expression analysis from a still dual facial view image. The system consists of three major parts: a facial data generator, a facial data evaluator and a facial data analyser. While the facial data generator applies fairly conventional techniques for facial feature extraction, the rest of the system represents a novel way of performing a reliable identification of 30 different face actions and a multiple classification of expressions into the six basic emotion categories. An expert system has been utilised to convert low level face geometry into high level face actions, and then this into highest level weighted emotion labels. The system evaluation results demonstrated rather high concurrent validity with human coding of facial expressions using FACS and formal instructions in emotion signals.","PeriodicalId":194023,"journal":{"name":"Proceedings 11th International Conference on Tools with Artificial Intelligence","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124217788","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A practical student model in an intelligent tutoring system","authors":"Yujian Zhou, M. Evens","doi":"10.1109/TAI.1999.809759","DOIUrl":"https://doi.org/10.1109/TAI.1999.809759","url":null,"abstract":"We consider two questions related to student modeling in an intelligent tutoring system: 1) what kind of student model should we build when we design a new system; and 2) should we divide the student model into different components depending on the information involved. We consider these two questions in the context of a conversational intelligent tutoring system, CIRCSIM-Tutor. We first analyze the range of decisions that the system needs to make and define the information needed to support these decisions. We then describe four distinct models that provide different aspects of this information, taking into consideration the nature of the domain and the constraints provided by the tutoring system. Finally, we briefly discuss our experiments with enhancing the student model in CIRCSIM-Tutor and some general problems regarding building and evaluating different student models.","PeriodicalId":194023,"journal":{"name":"Proceedings 11th International Conference on Tools with Artificial Intelligence","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123050173","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A formal basis for consistency, evolution and rationale management in requirements engineering","authors":"A. Ghose","doi":"10.1109/TAI.1999.809769","DOIUrl":"https://doi.org/10.1109/TAI.1999.809769","url":null,"abstract":"This paper presents a formal framework that addresses the twin problems of inconsistencies in requirements specifications and requirements evolution. It presents techniques (building on results from the areas of default reasoning and belief revision) for identifying maximal consistent subsets of a specification rendered inconsistent by a change step, with provision for retaining requirements that would be otherwise discarded, in anticipation of their future reuse. The paper identifies the need for consistent application of requirements rationale and provides support for this in the framework. While the problem of requirements evolution is intractable in the general case, tractable special cases exist within the framework. The paper also provides pointers to designing tools based on this framework.","PeriodicalId":194023,"journal":{"name":"Proceedings 11th International Conference on Tools with Artificial Intelligence","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123718782","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}